SemScape is an NLP-based framework for mining unstructured or free text. The ultimate goal of SemScape is to convert text into a machine-friendly structure, called TextGraph, which contains grammatical relations between terms and words in the text. In order to do so, SemScape uses linguistic morphologies to extract concepts and relations simultaneously.

The complete data stream management system must support relational streams, XML streams, and languages more powerful than SQL and XQuery--as required, e.g., for mining queries and queries for finding patterns in data streams.

-New mining algorithms

Poweful Archival Information Systems can be built by combining XML and relational DBs. XML supports a temporally-grouped view of the transaction-time history of the underlying DB, whereby powerful temporal queries are expressed in XQuery (with no extension required). Internally, RDBMSs support these temporal views and queries efficiently via SQL/XML.